Apache Mahout 0.6 发布

发布于 2012年02月07日
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Mahout是一个利用Map/Reduce的机器学习算法库,其思想源于斯坦福大学几个学者在2006年的nips会议上发表的一篇文章“Map- Reduct for Machine Learning on Multicore"

Apache Mahout 0.6 发布了,建议所有开发者升级,该版本主要改进包括:

  • Improved Decision Tree performance and added support for regression problems
  • New LDA implementation using Collapsed Variational Bayes 0th Derivative Approximation
  • Reduced runtime of LanczosSolver tests
  • K-Trusses, Top-Down and Bottom-Up clustering, Random Walk with Restarts implementation
  • Reduced runtime of dot product between vectors
  • Added MongoDB and Cassandra DataModel support
  • Increased efficiency of parallel ALS matrix factorization
  • SSVD enhancements
  • Performance improvements in RowSimilarityJob, TransposeJob
  • Added numerous clustering display examples
  • Many bug fixes, refactorings, and other small improvements

完整列表请看:release notes.

下载地址:Apache mirrors.

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本文标题:Apache Mahout 0.6 发布